Program Book - Waseda University
Transcript of Program Book - Waseda University
Theory and Applications of
Models of Computation
15th
Annual Conference on
Kitakyushu International Conference Center,
Kokura Station, Kitakyushu (City), Japan
13-16 April 2019
In Association with Proceedings published by
Professor Junzo Watada Professor Emeritus
Waseda University, Japan Chair, Programme Committee
IPS Graduate School, Waseda University, 2-7 Hibikino,
Wakamatsu. Kitakyushu 808-0135 JAPAN
Mobile: +81-90-3464-4929 E-Mail : [email protected]
Professor T V Gopal CEG Campus,
Anna University, Chennai, India Co-Chair, Programme Committee
Department of Computer Science and Engineering
College of Engineering Anna University
Chennai - 600 025, INDIA Ph : (Off) 22351723 Extn. 3340
Mobile: +91 9840121302 E-Mail : [email protected];
Program Book
Organization
Steering Committee Manindra
Agrawal
Indian Institute of Technology,
Kanpur, India
Jin -Yi Cai University of Wisconsin, USA
John Hopcroft Cornell University, USA
Ansheng Li Beihang University, Beijing,
China
Zhiyong Liu Institute of Computing
Technology, Chinese Academy
of Sciences, China
Conference and Program Committee Chair Junzo Watada Waseda University, Japan
Program Committee Co-chair T. V. Gopal Anna University, Chennai, India
Finance Committee Chair Yoshiyuki
Matsumoto
Shimonoseki City University,
Japan
Registration Committee Chair Yoshiyuki
Yabuuchi
Shimonoseki City University,
Japan
Registration Committee Co-Chair Hiroshi Sakai Kyushu Institute of Technology,
Japan
Program Committee Manindra
Agrawal
Indian Institute of Technology,
Kanpur, India
Klaus Ambos-
Spies
Heidelberg University, Germany
Abdel Monim
Artoli
King Saud University, Saudi
Arabia
Valentina Emilia
Balas
Aurel Vlaicu University of Arad,
Romania
Hans L.
Bodlaender
Utrecht University/Eindhoven
University of Technology, The
Netherlands
Anthony Bonato Ryerson University, Canada
Cristian S.
Calude
The University of Auckland,
New Zealand
Venkatesan
Chakaravarthy
IBM Research, India
Partha Pratim
Das
Indian Institute of Technology,
Kharagpur, India
Maya Dimitrova Institute of Robotics, Bulgarian
Academy of Sciences, Bulgaria
Antonio
Fernandez Anta
IMDEA Networks Institute,
Spain
Toshihiro Fujito Toyohashi University of
Technology, Japan
Wu Guohua Nanyang Technological
University
Kouichi Hirata Kyushu Institute of Technology,
Japan
John Hopcroft Cornell University, USA
Aaron D. Jaggard U.S. Naval Research Laboratory,
USA
Pushkar Joglekar Vishwakarma Institute of
Technology, Pune, India
Jan Kratochvil Charles University, Czech
Republic
Roman Kuznets TU Wien, Austria
Steffen Lempp University of Wisconsin-
Madison, USA
Angsheng Li
Zhiyong Liu
Beihang University
Institute of Computing
Technology, Chinese Academy
of Science, China
Johann
Makowsky
Technion Israel Institute of
Technology, Israel
Klaus Meer BTU Cottbus-Senftenberg,
Germany
Philippe Moser National University of Ireland,
Maynooth, Ireland
Masaaki
Nagahara
The University of Kitakyushu,
Japan
Pan Peng University of Sheffield,
Sheffield, UK
Jose Rolim University of Geneva,
Switzerland
Hiroshi Sakai
Yaroslav
Sergeyev
Kyushu Institute of Technology,
Japan University of Calabria,
Italy
Rudrapatna
Shyamasundar
Tata Institute of Fundamental
Research and Indian Institute of
Technology, Mumbai
Frank Stephan
Gopal Tadepalli
National University of Singapore,
Singapore Anna University, India
Junzo Watada Waseda University, Japan
Yoshiyuki
Yabuuchi
Shimonoseki City University,
Japan
Thomas
Zeugmann
Hokkaido University, Japan
Naijun Zhan Institute of Software, Chinese
Academy of Sciences, China
Akshay, S. Liu, Jiang
B. Krishna
Kumar
Meadows, Catherine
Fujiwara, Hiroshi N. R., Aravind
Ishii, Toshimasa Phawade, Ramachandra
Jiao, Li R. S. Bhuvaneswaran
Kar, Purushottam Rao, Raghavendra
Kimura, Kei Siromoney, Arul
Kucera, Antonin Xue, Bai
In Association with:
Preface
Theory and Applications of Models of Computation is a series of Annual Conferences
addressing all major areas in computer science; mathematics, especially logic; and physical
sciences, particularly with regard to computation and computability theory. The earlier
editions of these conferences were held at: TAMC 2004, Beijing; TAMC 2005, Kunming;
TAMC 2006, Beijing; TAMC 2007, Shanghai; TAMC 2008, Xi'an; TAMC 2009, Chang Sha;
TAMC 2010, Prague; TAMC 2011, Tokyo, Japan; TAMC 2012,Beijing, China; TAMC 2013,
Hong Kong, China., TAMC 2014, Chennai, India; TAMC 2015, Singapore; TAMC 2016 -
2017, Bern, Switzerland.
The 15th
Annual Conference TAMC 2019 was organized at Kitakyushu, Japan. The core
challenge is the complexity of describing problems in a logical formalism over finite
resources. Computational Models facilitate the discovery of the connections between the
computational complexity and the complexity of the problem formally specified.
The core team organizing TAMC 2019 was active over the past one year. The Call For Papers
attracted very good quality papers from 29 countries across the world. Professionals from 36
countries have been associated with TAMC 2019 as members of various committees, authors
and reviewers.
The Ministry for Human Resource Development, Government of India has decided to use
'Turnitin' software to curb "similarities" in Ph.D level publications. For practical use of this
policy, the following four color bands are being used in India.
1. Green: 1%to - 24% similarity index and means normal. or accepted
2. Yellow: 25-49% similarity index which is the second stage which means high
3. Orange (50-74% similarity index)
4. Red (75-100% similarity index)
Both iThenticate and Turnitin share the same underlying technology. The latter has a slant for
classroom work and hence less stringent. iThenticate is the last program in the series of
Turnitin programs. Leading academic institutions all over the world have adapted the
appropriate use of both these tools. Interpreting the results of "Similarity Check" software was
done with care and caution.
After the similarity check was completed 60 submissions went for reviews. Each submission
had two reviewers and there was spell of discussions. Finally 43 submissions were accepted
for inclusion in the proceedings and presentation during TAMC 2019. In addition, there are
six key – note addresses for professionals actively working in the areas related to TAMC
2019. Nearly 80% of the topics listed for TAMC series are covered in TAMC 2019.
TAMC 2019 was organized at the Kitakyushu International Conference Center which is the
core facility in the International Convention Zone, located in close proximity to the North Exit
of the JR Kokura Station. This innovative building, inspired by a ship’s bridge and choppy
waves, was designed by Isozaki Arata, one of Japan’s most world-renowned architects. The
wall facing the sea is made of glass, creating a wide open space that incorporates the maritime
scenery. The Main Hall and International Meeting Room are equipped with facilities for
simultaneous interpreting in 4 languages.
The conference team for TAMC 2019 thanks the key – note speakers, authors of the accepted
papers and all the members of various committees.
T.V.Gopal
Junzo Watada
PROGRAM SCHEDULE
13 April 2019
15:00-17:00 Registration
18:00-19:30 Warm Welcome
14 April 2019
8:00 Registration
9:00 Opening Ceremony
9:00-10:00 KEYNOTE Speech 1
Disruptive Innovation Based Schools – Are They Possible?
Maya Dimitrova (Institute of Systems Engineering and Robotics, Bulgarian Academy of
Sciences, Bulgaria)
10:00-11:00 KEYNOTE Speech 2
Rough Set Approaches to Data Mining
Masahiro Inuiguchi (Graduate School of Engineering Science, Osaka University, Japan)
11:00-11:30 Coffee Break
11:30-13:00 Battery Scheduling Problem
Aakash Agrawal, Krunal Shah, Amit Kumar, and Ranveer Chandra
The Volume of a Crosspolytope Truncated by a Halfspace - Ei Ando and Shoichi Tsuchiya
Computable Isomorphisms of Distributive Lattices - Nikolay Bazhenov, Manat Mustafa,
and Mars Yamaleev
Minmax-Regret Evacuation Planning for Cycle Networks - Robert Benkoczi, Binay
Bhattacharya, Yuya Higashikawa, Tsunehiko Kameda, and Naoki Katoh
Planar Digraphs for Automatic Complexity - Achilles A. Beros, Bjørn Kjos-Hanssen, and
Daylan Kaui Yogi
13:00 – 14:30 Lunch Break
14:00 – 15:30 Approximation Algorithms for Graph Burning - Anthony Bonato and Shahin Kamali
Sublinear Decoding Schemes for Non-adaptive Group Testing with Inhibitors - Thach V.
Bui, Minoru Kuribayashi, Tetsuya Kojima, and Isao Echizen
Compacting and Grouping Mobile Agents on Dynamic Rings - Shantanu Das, Giuseppe Di
Luna, Linda Pagli, and Giuseppe Prencipe
Maximum Independent and Disjoint Coverage - Amit Kumar Dhar, Raghunath Reddy
Madireddy, Supantha Pandit and Jagpreet Singh
Algorithms for Closest and Farthest String Problems via Rank Distance - Liviu P. Dinu,
Bogdan C. Dumitru, and Alexandru Popa
15:30-16:00 Coffee Break
16:00 – 17:30 Computable Analysis of Linear Rearrangement Optimization - Amin Farjudian
On the Power of Oritatami Cotranscriptional Folding with Unary Bead Sequence -
Szilárd Zsolt Fazekas, Kohei Maruyama, Reoto Morita and Shinnosuke Seki
Stochastic Programming for Energy Plant Operation - Tomoki Fukuba, Takayuki Shiina,
and Ken-ichi Tokoro
Compact I/O-Efficient Representation of Separable Graphs and Optimal Tree Layouts -
Tomáš Gavenčiak and Jakub Tětek
Unshuffling Permutations: Trivial Bijections and Compositions - Guillaume Fertin,
Samuele Giraudo, Sylvie Hamel and Stéphane Vialette
17:30-18:00 Coffee Break
18:00 – 19:30 Continuous Team Semantics - Åsa Hirvonen, Juha Kontinen, and Arno Pauly
Exact Satisfiabitity with Jokers - Gordon Hoi, Sanjay Jain, Sibylle Schwarz, and Frank
Stephan
Theoretical Model of Computation and Algorithms for FPGA-Based Hardware
Accelerators - Martin Hora, Václav Končický, and Jakub Tětek
On the Complexity of and Algorithms for Min-Max Target Coverage On a Line
Boundary - by Peihuang Huang, Wenxing Zhu, and Longkun Guo
Online Travelling Salesman Problem on a Circle - Vinay A. Jawgal, V. N. Muralidhara, and
P. S. Srinivasan
15 April 2019
8:00 Registration
9:00-10:00 KEYNOTE Speech 3
Approach to Machine Learning without Neural Networks
Akihiro Yamamoto (Gradudate Scool of Informatics, Kyoto University, Japan
10:00-11:00 KEYNOTE Speech 4
Fuzzy Cognitive Maps in Modelling Real Life Problems
Laszlo T. Koczy (Budapest University of Technology and Economics and Szechenyi Istvan
University (Gyor), Hungary
11:00-11:30 Coffee Break
11:30-13:30 Second-Order Linear-Time Computability with Applications to Computable Analysis -
Akitoshi Kawamura, Florian Steinberg, and Holger Thies
Consistency as a Branching Time Notion - Astrid Kiehn and Mohnish Pattathurajan
Finite Choice, Convex Choice and Sorting - Takayuki Kihara and Arno Pauly
The Number of Languages with Maximum State Complexity - Bjørn Kjos-Hanssen and Lei
Liu
Deterministic Coresets for Stochastic Matrices with Applications to Scalable Sparse
PageRank - Harry Lang, Cenk Baykal, Najib Abu Samra, Tony Tannous, Dan Feldman, and
Daniela Rus
GPU Based Horn-Schunck Method to Estimate Optical Flow and Occlusion - Vanel
Lazcano and Francisco Rivera
Robot Computing for Music Visualization - Pei-Chun Lin, David Mettrick, Patrick C. K.
Hung, and Farkhund Iqbal
Combinatorial Properties of Fibonacci Arrays - Manasi S. Kulkarni, Kalpana Mahalingam,
Sivasankar Mohankumar
13:30 – 14:30 Lunch Break
14.30 Half Day Tour
Departure at the exit of the International Conference Hall at 14.30
18:30 Banquet "Marrygold Mojiko Geihinkan"
20:30 Bus Returning to Convention Center / Kokura Station
16 April 2019
8:00 Registration
9:00-10:00 KEYNOTE Speech 5
Structural Information Theory and Its Applications
Angsheng Li State Key Laboratory of Software Development Environment, School of Computer
Science, Beihang University, China
10:00-11:00 KEYNOTE Speech 6
Unconventional Proving Techniques in Cyber – Physical Systems
Dr. T V Gopal, Department of Computer Science and Engineering, College of Engineering
Anna University, India
11:00-11:30 Coffee Break
11:30-13:00 Watson-Crick Jumping Finite Automata - Kalpana Mahalingam, Rama Raghavan, Ujjwal
Kumar Mishra
Dispersion of Mobile Robots: The Power of Randomness - Anisur Rahaman Molla and
William K. Moses Jr.
Building Resource Auto-scaler with Functional-Link Neural Network and Adaptive
Bacterial Foraging Optimization - Thieu Nguyen, Binh Minh Nguyen, and Giang Nguyen
On the Enumeration of Bicriteria Temporal Paths - Petra Mutzel and Lutz Oettershagen
An Output-Sensitive Algorithm for the Minimization of 2-Dimensional String Covers -
Alexandru Popa and Andrei Tanasescu
13:00 – 14:30 Lunch Break
14:00 – 15:30 Introducing Fluctuation into Increasing Order of Symmetric Uncertainty for
Consistency-Based Feature Selection - Sho Shimamura and Kouichi Hirata
Card-Based Cryptography with Invisible Ink - Kazumasa Shinagawa
Read-Once Certification of Linear Infeasibility in UTVPI Constraints - K. Subramani and
Piotr Wojciechowski
Generalizations of Weighted Matroid Congestion Games: Pure Nash Equilibrium,
Sensitivity Analysis, and Discrete Convex Function - Kenjiro Takazawa
The Complexity of Synthesis for 43 Boolean Petri Net Types - Ronny Tredup and Christian
Rosenke
15:30-16:00 Coffee Break
16:00 – 17:30 Space Lower Bounds for Graph Stream Problems - Paritosh Verma
Bounded Jump and the High/Low Hierarchy - Guohua Wu and Huishan Wu
Supportive Oracles for Parameterized Polynomial-Time Sub-Linear-Space Computations
in Relation to L, NL, and P - Tomoyuki Yamakami
Dynamic Average Value-at-Risk Allocation on Worst Scenarios in Asset Management -
Yuji Yoshida and Satoru Kumamoto
First-Order vs. Second-Order Encodings for LTLf -to-Automata Translation - Shufang
Zhu, Geguang Pu, and Moshe Y. Vardi
17:30 Closing Session
Keynote Speech
Maya Dimitrova Institute of Systems Engineering and
Robotics, Bulgarian Academy of Sciences
Bulgaria
Topic : Disruptive Innovation Based Schools – Are They Possible?
Abstract : In the school of the future each teacher or a team of teachers, instead of paper and pencil tools,
can have an array of tools - robotic scenarios, Virtual Reality based demonstrations and
intelligent lesson-enhancing advice systems - to design up-to-date attractive and entertaining
educational courses. Moreover, intelligent desks will be able to monitor gaze direction and
count blinks in order to define moments in the lesson when the attention of the student is
optimal. By knowing the attentional dynamics it is possible to modify the lesson to avoid
repetition, yet provide additional help for the unlearned material. The lessons will be deeply
individualized and adapted to the student learning difficulties, or talents, and will include even
less in number examination tests. In such a classroom no students will be delayed by the
others, or intimidated by being slower than the group. In such a scenario the social
communication between the children will be supported and will not be based on competition,
but on collaboration and mutual care.
The keynote speech will focus on the main ideas and results of the ongoing H2020-MSCA-
RISE-2017 project “CybSPEED: Cyber-physical systems for pedagogical rehabilitation in
special education”, involving researchers from Bulgaria, Greece, France, Spain, Japan, Chile
and Morocco, and the main lessons learned in the context of introducing disruptive innovation
in the school of the future.
The book “Cyber-physical systems for social applications” is oriented towards achieving these
aims by providing relevant theoretical frameworks and the latest empirical findings in the
areas of designing socially-oriented cyber-physical systems.
Biography : Maya Dimitrova received her higher education in psychology from St Petersburg, Russia, in
1885. She obtained her MSc in psychology (by research) (with distinction) from Warwick
University, UK, in 1995 and her PhD on Adaptive Human Computer Interface from Institute
of Control and Systems Research at BAS in 2002. She is currently Associate Professor at the
Institute of Robotics at BAS, working on humanoid robotics for learners with special needs.
Since 2017 she engaged with an EU funded project CybSPEED on “Cyber-physical systems
for pedagogical rehabilitation in special education
Keynote Speech
Masahiro Inuiguchi Graduate School of Engineering Science
Osaka University
Japan
Topic : Rough Set Approaches to Data Mining
Abstract : Rough set theory provides useful tools for reasoning from data. Attribute reduction and rule
induction are well developed techniques based on rough set theory. They are applied to various
fields including data analysis, signal processing, knowledge discovery, machine learning,
artificial intelligence, medical informatics, decision analysis, granular computing, Kansei
engineering, and so forth. In the approach, the lower approximation (a set of objects whose
classification is consistent in all given data) and upper approximation (a set of possible
members in view of given data) are calculated for each decision class.
In this talk, we introduce rough set approaches to data analysis. After describing fundamentals
of the classical rough sets, several methods for attribute reduction and minimal length rule
induction are introduced. Then generalization and extension of rough set approaches are
shown. First, we describe relation-based generalizations of rough sets and data analysis based
on them. In these approaches, the indiscernibility relation which is an equivalence relation in
the classical rough sets is generalized to any relation. General approaches from two different
viewpoints are described. Two special cases, i.e., rough set approaches under dominance
relation and missing values, demonstrate the usefulness of the approaches. Second, we extend
the classical rough set approaches to the analysis of imprecise decisions. By considering the
imprecise decisions, we show that a hierarchy of attribute reduction and a different aspect of
attribute importance can be analyzed. Moreover, we demonstrate that a set of imprecise
decision rules works better than a set of precise decision rules. This property is applied to a
privacy protection in data publication. Throughout this talk, we show the ideas of rough set
approaches potentially applicable to various fields involving data analysis.
Biography : Masahiro Inuiguchi received B.E., M.E. and D.E. degrees in industrial engineering at Osaka
Prefecture University, in 1985, 1987 and 1991. He worked as a Research Associate at Osaka
Prefecture University (1987-1992), Associate Professor at Hiroshima University (1992-1997),
Associate Professor at Osaka University (1997-2003). At present, he is a Full Professor at
Osaka University. His interests include possibility theory, fuzzy programming, rough sets and
multiple criteria decision analysis with interval models. He works as area editor of Fuzzy Sets
and Systems (FSS), Fuzzy Optimization and Decision Making (FODM), and Journal of
Multiple Criteria Decision Analysis (MCDA), as the associate editor of ITOR and 4OR, and
members of editorial boards of several other Journals including EJOR.
Keynote Speech
Akihiro Yamamoto Gradudate Scool of Informatics
Kyoto University
Japan
Topic : Approach to Machine Learning without Neural Networks
Abstract : Because of the great success of deep learning, many imagine that machine learning should be
implemented with neural networks well-structured for data which they would like to analyze.
Going back to the original meaning of machine learning, we should be allowed construct
learning mechanism without neural networks. In particular neural networks are suited for real
valued vector data, but are not always for discrete structured data. Discrete structured data,
such as character sequences, trees, and graphs, have mathematical theories and algorithms
particular to each, and learning algorithms treating such data should be designed based on the
theories and algorithms.
In this talk we would introduce recent results on learning from discrete structured data. The
first type of data are trees. In order to apply the idea of principle component analysis to tree
data, we investigate fast computation methods for computing distances between trees by using
integer programming technique. Second we report a result on learning logical formulae in
first order logic, which has been called inductive logic programming. Recent developments of
computing Boolean functions could be applied for various types of secrete data, and logical
formulae should be of such types. We show how binary decision diagrams should be applied
to inductive logic programming.
Biography : Akihiro Yamamoto received the B.S. degree from Kyoto University in 1985, and the M.S. and
Dr.Sci. degrees from Kyushu University in 1987 and 1990 respectively. From 1990 to 2003 he
was an associate professor at Hokkaido University. He was also a researcher of PREST at
JST, and a visiting researcher at Oxford University and Technische Hochschule Darmstadt.
Since October 2003 he has been a professor of Graduate School of Informatics, Kyoto
University. From April 2015 to March 2018 he was the dean of the school. Since April 2018
he has also held the position of the director of Center for Innovative Research and Education
in Data Science.
His research interest Includes foundations of Machine Learning and Data Mining, in
particular, with theory of computation, mathematical logic, and computational algebra.
Keynote Speech
Laszlo T. Koczy Budapest University of Technology and Economics
1111 Budapest,
Műegyetem rkp. 3.
and
Szechenyi Istvan University (Gyor)
H-9026 Győr, Egyetem tér 1., Hungary
Topic : Fuzzy Cognitive Maps in Modelling Real Life Problems
Abstract : Fuzzy Cognitive Maps (FCM) are a set of tools merging the properties of Artificial Neural
Networks (NN) and fuzzy systems. They are bipolar directed fuzzy graphs that consist of
Concepts (nodes) assigned fuzzy membership degrees expressing the intensity or level of the
property associated with the given concept; and of directed influence values (edges) which
have a sign (expressing whether the influence is positive or negative) and a fuzzy membership
degree of the intensity of the influence. E.g., if C1 and C2 are two concepts, µ1 is the degree of
C1 and µ2 of C2, the directed edges e12 and e21 have ± µ12 and ± µ21, respectively, denoting that
C1 influences C2 either in the positive sense (increasing its level) with + µ12, or in the negative
sense (decreasing C2) with - µ12. FCMs are suitable to model multicomponent systems with
multiple mutual influences, such as, e.g. a management system. Because of the NN-type
behaviour of FCMs, they may be used for simulating a system that changes in time, and
possibly converges to a steady state (called fixed point attractor). It is interesting to fit the
FCM to a series of historical data and calculate the expected development of the system in the
future – a way for time series prediction. Such fitting may happen by various machine
learnning techniques, such as evolutionary and memetic algorithms, among others. In this case
the FCM model will be determined by theis fitting, including all membership degrees at the
concepts and at the edges. On the other hand, often experts determine these values
(approximately) in advance, and thus the FCM model is ready for prediction - starting from a
known initial state.
In our past reserch we found real life applications (such as waste management, bank
management, etc.) where one or both of the starting data were available. Especially interesting
is the case when experts determine the membership degrees and then the FCM is matched to
the historical data. In some case we found contradiction in the contents and this fact started a
deeper methodological research about how to fit the proper FCM to a given problem, and how
to transform the size and complexity of such models, so that theyt reemain intuitive, and
tyransparent, while the fineness and precision of the model is satisfactory from the point of
view of the application field.
This talk will give some formal definitions in connection with FCMs, and then show the
iterative (NN-like) behaviour. The next question to be discussed will be the existence and
number of fixed point attractors (sustainable state of the system to be modelled), a topic that
has not yet been satisfactorily clarified in the literature. In this respect we have presented some
entirely new results in the form of mathematical statements.
In the next a novel extension, the Fuzzy Grey Cognitive Map will be introduced, and it will be
shown that they are more adequate in modelling real life systems, as human experts often
hesitate in giving concrete degrees, and subjectivity and uncertainty of the experts prevent any
clear and deterministic membership values at the concepts and edges. The next real application
motivated extension is the application of fuzzy numbers for determining the memberships.
Some results about the existense and uniqueness of a fixed point attractor are also stated here.
The other main stream of the research reported here focuses on the transformation of FCMs (as
far in the classic sense), especially by reducing the size of the model, namely, the number of
concepts, which of course also results in the drastic reduction of the number of edges in the
new model. A novel reduction technique, based on a very special FCM compatible metrics (a
distance measure between two concepts where all the influence degrees to other concepts and
the way around are known and compared) is proposed, illustrated by a real life problem, where
the obvious contradiction between the expert assessment and the historical data points towrds
the necessity of the refinement of the mmodel, and then, towards a transformation that leads to
the emerging of new concepts that have to be interpreted in the context of the application
problem. An extensive simulation, applying a large number of real life and randomly generated
examples for large size FCMs and respective reductions allows the discussion of to what
extent such a transformation preserves the properties of the original FCM, with a special stress
on the existence, number and parameters of the fixed points.
The last topic of the talk is about the sensitivity of the FCMs, where it may be assumed that
expert assessments are subjective and uncertain, and the uncertainty or error in the
membership values may cause instability, even, a total change of behaviour of the FCM. One
more real life example will be presented and evaluated.
Some future directions of further related research goals will be proposed at the end of the talk.
Biography : Laszlo T. Koczy received the M.Sc., M.Phil. and Ph.D. degrees from the Technical University
of Budapest (BME) in 1975, 1976 and 1977, respectively; and the D.Sc. degree from the
Hungarian Academy of Science in 1998. He spent his career at BME until 2001, and from
2002 at Szechenyi Istvan University (Gyor, SZE). He has been from 2002 to 2011 Dean of
Engineering, and from 2013 to current, President of the University Research Council and of
the University Ph.D. Council. From 2012 he has been a member of the Hungarian
Accreditation Committee (for higher education), appointed by the Prime Minister, and elected
Chair of the Engineering and Computer Science sub-committee, Acting Chair of the Professors
and Ph.D. sub-committee, and has been a member of the National Doctoral Council since
2012.
He has been a visiting professor in Australia (ANU, UNSW, Murdoch and Deakin), in Japan
(TIT, being LIFE Endowed Fuzzy Theory Chair Professor), in Korea (POSTECH), Austria (J.
Kepler U.), Italy (U. of Trento), and Poland (AGH University) etc.
His research interests are Intelligent Modeling and algorithms with multidisciplinary
applications including management and logistics. He has published over 620 articles, most of
those being refereed papers, and several text books on the subject. He has over to 2727
independent citations (mtmt.hu) and his Hirsch-index is 37 by Google Scholar (based on
~5626 citations there).
His main results are: he did introduce the concept of rule interpolation in sparse fuzzy models,
and hierarchical interpolative fuzzy systems, fuzzy Hough transform, and also fuzzy signatures
and fuzzy situational maps, further fuzzy signature state machines among others. He also
proposed a family of memetic algorithms (Bacterial Memetic Algorithm, Discrete Bacterial
Memetic Algorithm) which, among others, provides the best solutions to the Traveling
Salesman Problems and Traveling Repairman Problems. His research interests include
applications of CI for management, transportation and logistics, control and decision support
information retrieval, etc.
He was a Lead Guest Editor at Complexity. He was an Associate Editor of IEEE TFS for
several periods, and is now AE of Fuzzy Sets and Systems, Int. Journal of Fuzzy Systems,
Journal of Advanced Computational Intelligence, Int. J. of Fuzzy Systems, Soft Computing,
etc. He is a Fellow of International Fuzzy Systems Association, of International Society of
Management Engineers and of the Hungarian Academy of Engineering. He was the founding
President and is now the Life Honorary President of the Hungarian Fuzzy Association, was
President, etc. of IFSA, AdCom member of IEEE CIS, and of IEEE Systems Council, etc.
He is a member of the St. Stephan Academy of Science (2016), and of the Polish Academy of
Science (2017)
Keynote Speech
Angsheng Li State Key Laboratory of Software Development Environment,
School of Computer Science, Beihang University,
100083 Beijing, P.R. China
Topic : Structural Information Theory and Its Applications
Abstract : Shannon 1948 defined the metric of the entropy of a probability distribution or a random
variable. The Shannon's theory answers two fundamental questions in communication theory,
the ultimate data compression (entropy) and the ultimate transmission rate of communication
(the channel capacity defined by using mutual information). Shannon's theory started the
classical information theory, providing the principle for us to understand the notion of
information in the current science. The current Computer Science has become very much
different from that in the last century in that, computer plays an important role in almost every
aspect of our life and our world, instead of simply "computing".
The current computer has changed its role from "computing of functions " to "information
processing" in a wider range of the universe such as massive graphs, and structured or
unstructured noisy data. The classic information theory, studying the principles of the simple
objects of random variables (which are actually functions), is apparently insufficient to support
the "information processing" of the current computer science, due to the fact that the universe
of computer information processing is much larger than that of the Shannon information
theory.
A grand challenge is hence: Is there a theory that supports the information processing of the
current computer? The key to this question is to define the information that is embedded in a
system such that the information of the system distinguishes the laws from the noises of the
system.
Recently, we proposed the notion of encoding tree of graphs and the notion of structural
entropy, and established the fundamental theory of the structural information.
Angsheng Li is a Professor of Beihang University, School of Computer Science from 2018,
July. He was research professor of Institute of Software, Chinese Academy of Sciences from
1999 to 2018, July. He was born in 1964. He got bachelor in Mathematics in Yunnan Normal
University in 1984, and ph D in 1993 in Institute of Software, Chinese Academy of Sciences.
He had been working for the Institute of Software, Chinese Academy of Sciences from 1993 to
2018, July after he finished his ph D. From 1998 to 2002, he was a visitor and research fellow
in the University of Leeds, UK, working with Professor Barry Cooper in Computability
Theory. In 2003, he was awarded the Distinguished Young Investigator award of the National
Natural Science Foundation of China. In 2008, he was selected by the Hundred Talent
Program of Chinese Academy of Sciences. From 2008 to 2009, he was a visiting scientist in
Computer Science Department, Cornell University, US, working with Professor Juris
Hartmanis (the founder of Computational Complexity Theory). His research areas include
Computability Theory, Computational Theory, Network Theory and Information Science. His
current interests focus on massive graph algorithms, information theory, and information
theoretical foundation of artificial intelligence.
Keynote Speech
Dr. T V Gopal Professor
Department of Computer Science and Engineering
College of Engineering
Anna University
Chennai - 600 025, INDIA
Topic : Unconventional Proving Techniques in Cyber – Physical
Systems
Abstract : Cyber - Physical Systems [CPS] are “Engineered systems that are built from, and depend
upon, the seamless integration of computational algorithms and physical components”. CPS
have the potential to provide much richer functionality - including efficiency, flexibility,
autonomy, and reliability – than systems that are loosely coupled, discrete, or manually
operated. CPS also can create vulnerability related to protection, security and reliability. This
can result in a chaotic collapse around the many new complex and powerful technological
systems we rely on. The very complexity and interconnectedness of such CPS warrants
unconventional proofing to unravel. Moreover, CPS is diffused across the social fabric. The
sociology of mathematics is quite elusive for the construction of formal proofing in CPS.
The gap between rigorous argument and formal proof in the sense of mathematical logic is one
that will close in CPS.
The frightening possibility is that the question of what is a proof may reach the law courts.
What does it mean when mainstream explanations of our physical reality are based on what
even scientists cannot comprehend? The generic characteristics of CPS are:
Self-organization
Interdependence
Feedback
Far from equilibrium
Exploration of the space of possibilities
History and path dependence
Creation of new order
Cyber risk is an increasing concern in the complex, connected world of CPS. The complexity
of the ecosystem, the connectivity of devices and the criticality of devices and services all
increase risk, and the necessary formal proofs are elusive to take an effective action. „Fake
People” is the Case Study presented in this address to illustrate unconventional proofing in
Humane Security Engineering of CPS.
References:
1. Gopal T V, "The Physics of Evolving Complex Software Systems", International
Journal of Engineering Issues [IJEI], Vol. 2015, no. 1, pp. 33-39.
2. Gopal T V, "Modeling Cyber - Physical Systems for Engineering Complex
Software",, International Journal of Engineering Issues [IJEI], Vol. 2015, no. 2, pp.
73-78.
3. Gopal T V,"Engineering Software Behavior in Cyber – Physical Systems",
International Journal of Engineering Issues [IJEI], Vol. 2016, no. 1, pp. 44-52.
4. Gopal T V, "Engineering Logic for Cyber – Physical Systems", International Journal
of Engineering Issues, Vol. 2016, no. 3,pp. 112-120.
5. Gopal T.V. „Beautiful code – circularity and anti-foundation axiom‟, Int. J.
Computational Systems Engineering, Vol. 2, No. 3, 2016, pp.148–154.
6. Gopal T V, “Communicating and Negotiating Proof Events in the Cyber – Physical
Systems”, International Journal of Advanced Research in Computer Science and
Software Engineering, Volume 7, Issue 3, March 2017, pp 236-242.
7. Gopal T. V, Cyber-Physical Systems and Humane Security Engineering, Journal of
Network and Information Security, Vol. 6, No. 2, December 2018, pp 24-31
8. Reuben Hersh (Editor), “18 Unconventional Essays on the Nature of Mathematics,
Springer; 2006.
Biography : Dr. T V Gopal is presently teaching Computer Science and Engineering at the CEG Campus,
Anna University. One of his research areas includes "Science and Spirituality". Dr. T V Gopal
has published around 75 Research Papers. He has written four books and Co-Edited Seven
Conference Proceedings. He is actively associated with many professional societies such as
CSI, IEEE and ACM India Council. He is an Expert Member of the Editorial Advisory Board
of the International Journal of Information Ethics. For further details, please visit:
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